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Panel
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Tue 10:00
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Panel 1C-5: Privacy of Noisy… & Near-Optimal Private and…
Shyam Narayanan · Kunal Talwar
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Workshop
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Sat 7:30
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Invited Talk: Virginia Smith - Practical Approaches for Private Adaptive Optimization
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Poster
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Tue 9:00
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Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization
Liang Zhang · Kiran Thekumparampil · Sewoong Oh · Niao He
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Workshop
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Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses & Extension to Non-Convex Losses
Andrew Lowy · Meisam Razaviyayn
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Workshop
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Differentially Private Adaptive Optimization with Delayed Preconditioners
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith
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Workshop
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Differentially Private Adaptive Optimization with Delayed Preconditioners
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith
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Poster
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Tue 14:00
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Differentially Private Online-to-batch for Smooth Losses
Qinzi Zhang · Hoang Tran · Ashok Cutkosky
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Poster
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Thu 9:00
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Momentum Aggregation for Private Non-convex ERM
Hoang Tran · Ashok Cutkosky
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Poster
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Thu 9:00
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Differentially Private Generalized Linear Models Revisited
Raman Arora · Raef Bassily · Cristóbal Guzmán · Michael Menart · Enayat Ullah
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Poster
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Thu 9:00
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Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
Sergey Denisov · H. Brendan McMahan · John Rush · Adam Smith · Abhradeep Guha Thakurta
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Poster
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Tue 9:00
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SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression
Zhize Li · Haoyu Zhao · Boyue Li · Yuejie Chi
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Poster
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Thu 9:00
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When Does Differentially Private Learning Not Suffer in High Dimensions?
Xuechen Li · Daogao Liu · Tatsunori Hashimoto · Huseyin A. Inan · Janardhan Kulkarni · Yin-Tat Lee · Abhradeep Guha Thakurta
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